War-Game Your AI Projects to Eliminate the Last 20% of Manual Rework
Plans get you 80% done; the last 20% is where projects die. Instead of asking AI for better plans, have it 'war-game' every step—mapping action, reaction, and counteraction for each failure mode—then hand those pre-simulated decision trees to execution models that can now handle the hard part without manual firefighting.
“We see this same pattern in manufacturing: process plans that work in theory but fail at edge cases. Building failure modes into the design upfront—exactly what FMEA does on the plant floor—can cut rework and firefighting by 30-50% in our implementations.”
Plans get you 80% done; the last 20% is where projects die. Instead of asking AI for better plans, have it 'war-game' every step—mapping action, reaction, and counteraction for each failure mode—then hand those pre-simulated decision trees to execution models that can now handle the hard part without manual firefighting.
From the Source
"A war-game would basically say, 'Use this plan, but assume that at every juncture, there's going to be a couple different possible scenarios. Based on your experience, how would you handle those scenarios?'"
— Do THIS Before You Lose Access to Fable 5
Key Takeaways
- 01Standard AI plans complete ~80% of a project, leaving the hardest 20% for manual intervention and rework
- 02Use advanced models (like Fable) for war-gaming simulations, not basic planning—it's a waste of 'valuable tokens' otherwise
- 03Structure every move with: expected observation, most likely failure, failure signals, countermove, and abort conditions
- 04Bulk-generate war-game files, then feed them to execution models (Opus 4.8, GPT 5.5) for confident, edge-case-aware implementation
- 05Include second and third-order consequences to anticipate failures 'a few layers down from the initial action'
Watch the Source
Do THIS Before You Lose Access to Fable 5
Source
Do THIS Before You Lose Access to Fable 5
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